#AI & #ML Lecture 9 : Supervised Evaluation, K-Fold Cross Validation & Multiclass Classification

#ArtificialIntelligence #MachineLearning #Software #Engineering #Course Hello everyone. My name is Furkan Gözükara, and I am a Computer Engineer Ph.D. Assistant Professor at the Software Engineering department.

In this course, starting from ground to the advanced level Artificial Intelligence and Machine Learning course will be taught.

Artificial Intelligence (AI) and Machine Learning (ML) Full Course with C# Examples Playlist : https://www.youtube.com/playlist?list=PL_pbwdIyffskVschrADCL6KEnL_nqDtgD

GitHub repository of the course : https://github.com/FurkanGozukara/CSE419-Artificial-Intelligence-and-Machine-Learning-2020

Discord channel link of the course : https://discord.gg/6Mrb8MwteQ How to use Discord : https://youtu.be/AEwPtYiLvsQ

Lecture 9: Evaluation and Multi-class Classification ** Evaluation

• Supervised evaluation
• Comparing algorithms
• Idea 1
• Is model 2 better?
• Comparing scores: significance
• Idea 2
• Variance
• Repeated experimentation
• n-fold cross validation
• k-fold cross validation
• Leave-one-out cross validation
• Comparing systems: sample 1
• Comparing systems: sample 2
• Comparing systems: sample 3
• Comparing systems
• Comparing systems: sample 4
• Statistical tests
• F1-Score (F-Score)
• t-test
• Calculating t-test
• p-value
• Statistical tests on test data
• Bootstrap resampling
• Experimentation good practices ** Multiclass
• Multiclass classification
• Real world multiclass classification
• Multiclass: current classifiers
• k-Nearest Neighbor (k-NN)
• Decision Tree learning
• Perceptron learning
• Black box approach to multiclass
• Approach 1: One vs. all (OVA)
• OVA: linear classifiers (e.g. perceptron)
• OVA: classify
• OVA: classify, perceptron
• Approach 2: All vs. all (AVA)
• AVA training visualized
• AVA classify
• OVA vs. AVA
• Approach 3: Divide and conquer
• Multiclass summary
• Multiclass evaluation
• Multiclass evaluation imbalanced data
• Macro averaging vs. micro averaging
• Confusion matrix

This course requires you to be knowing a programming language or be able to utilize an Artificial Intelligence and Machine Learning tool.

Therefore, if you want to start learning to program or develop your other Software Engineering related skills, you can watch our below full courses:

[1] Introduction to Programming Full Course with C# playlist : https://www.youtube.com/playlist?list=PL_pbwdIyffskoSXySh0MdiayPJsBZ7m2o

[2] Object Oriented Programming Full Course with C# playlist : https://www.youtube.com/playlist?list=PL_pbwdIyffsnH3XJb66FDIHh1yHwWC26I

[3] Artificial Intelligence (AI) and Machine Learning (ML) Full Course with C# Examples playlist: https://www.youtube.com/playlist?list=PL_pbwdIyffskVschrADCL6KEnL_nqDtgD

[4] Software Engineering Full Course playlist : https://www.youtube.com/playlist?list=PL_pbwdIyffslgxMVyXhnHiSn_EWTvx1G-

[5] Security of Information Systems Full Course playlist : https://www.youtube.com/playlist?list=PL_pbwdIyffslM_o92NwkaUzD7C6Fekx26

[6] (Turkish) Bilgisayar Becerileri Tam Ders playlist : https://www.youtube.com/playlist?list=PL_pbwdIyffsmyE2e909ea1MXLcMb8MenG

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